Energy Storage System Modeling and Control

Wei, Liu

doi:10.1002/9781118407400.ch5

Cited by 2 publications

(2 citation statements)

References 11 publications

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“…The NSGA optimizations are performed with a minimum pinch value constraint of 5°C in order to limit the evaporator exchange surface. 36–38 Note that the pressure drop in the ORC system is neglected as it contributes to only 0.6% drop in the overall efficiency. The negligible impact of the pressure drop on the efficiency is due to the advantage of using the R-1234yf working fluid, which circulates in the liquid–gas form in the system.…”

Section: Orc Modelmentioning

confidence: 99%

“…A NiMH battery with a 1.1-kWh energy capacity is considered as a buffer and represented by a simple battery model of voltage source and internal resistance with a coulombic efficiency of 95%. 39 The vehicle chassis corresponds to a mass-production C-segment vehicle with a weight of 1474 kg. The ORC system illustrated in Figure 1 is integrated in the vehicle model, and the energy recovered from the coolant is converted into electrical energy through a 70% efficiency electric generator and stored in the battery.…”

Section: Mild Hybrid Vehicle Modelmentioning

confidence: 99%

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Waste heat recovery from engine coolant on mild hybrid vehicle using organic Rankine cycle

Mansour

Nader

Dumand

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part D:

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Considerable efforts have been invested in the automotive industry on electrified powertrains in order to reduce passenger cars’ dependence on fossil fuels. Powertrains electrification resulted in a wide range of mass-production hybrid vehicle models, ranging from micro-hybrid, to mild, full, and battery-extended hybrids such as plug-in and range-extender electric vehicles. Fuel savings of these powertrains strongly rely on the energy management strategy deployed on-board, as well as on the technology used to recover the waste heat energy. This paper investigates the fuel savings potential of a mild hybrid vehicle using an organic Rankine cycle for generating electricity from the engine-coolant circuit. The net mechanical power and electrical power generated from the organic Rankine cycle are determined based on experimental data recorded on a 1.2-L turbocharged engine. The coolant temperature is regulated at 85°C and 105°C depending on the engine load. The R-1234yf organic fluid is used and the Rankine operating pressure has been controlled to maximize the overall system efficiency under technological constraints. The dynamic programming control is used as a global optimal energy management strategy in order to define the best strategy for the engine operation and power-split between the electric and thermal paths of the powertrain. A sensitivity analysis is also performed to find the optimal size of the electric motor while taking into account the additional weight of the organic Rankine cycle system. Results show 2.4% of fuel economy improvement on The Worldwide Harmonized Light Vehicles Test Cycles.

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Section: Orc Modelmentioning

confidence: 99%

Section: Mild Hybrid Vehicle Modelmentioning

confidence: 99%

Waste heat recovery from engine coolant on mild hybrid vehicle using organic Rankine cycle

Mansour

Nader

Dumand

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part D:

View full text Add to dashboard Cite

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Trip-based optimization methodology for a rule-based energy management strategy using a global optimization routine: the case of the Prius plug-in hybrid electric vehicle

Mansour

2016

Proceedings of the Institution of Mechanical Engineers, Part D:

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The fuel savings of plug-in hybrid electric vehicles strongly rely on the energy management strategy deployed onboard. For the current mass-produced plug-in hybrid electric vehicles, notably the Toyota Prius, the energy management strategy is a rule-based type, which is configured to optimize instantly the fuel consumption without taking into consideration the upcoming driving patterns of the given route schedule. Hence, it operates the vehicle first in the electric mode over a predefined all-electric range and then in the charge-sustaining mode. The energy consumption results are seen to be far from optimal when compared with global optimization strategies with prior knowledge of the scheduled route, such as dynamic programming. Hence, this study presents the methodology to optimize the rule-based energy management strategy for real-time implementation in the Prius plug-in hybrid electric vehicle, using dynamic programming as the global optimization routine. The optimization process takes into account the desired trip profile selected by the driver on the vehicle’s onboard Global Positioning System and linked to a traffic management system. A basic rule-based energy management strategy, which emulates the vehicle performance and the energy consumption, has been set first using on-road measurement data logging. As a second step, the dynamic programming optimization routine was applied to the model, assuming a repeated New European Driving Cycle as the scheduled route. The results obtained for the behaviours of the powertrain components under optimal control are evaluated and used to update the operating energy management rules of the basic controller. Finally, an optimized rule-based controller is proposed by coupling between the dynamic programming and the basic rule-based controller, followed by an evaluation of the energy consumption and the powertrain efficiency of the three investigated control strategies.

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Energy Storage System Modeling and Control

Cited by 2 publications

References 11 publications

Waste heat recovery from engine coolant on mild hybrid vehicle using organic Rankine cycle

Waste heat recovery from engine coolant on mild hybrid vehicle using organic Rankine cycle

Trip-based optimization methodology for a rule-based energy management strategy using a global optimization routine: the case of the Prius plug-in hybrid electric vehicle

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